mapview

library(sf)
library(mapview)

ciclovias_2016 <- read_sf("http://datos.cedeus.cl/geoserver/wfs?srsName=EPSG%3A4326&typename=geonode%3Aciclovias_existentes_09_16&outputFormat=json&version=1.0.0&service=WFS&request=GetFeature")
ciclovias_2018 <- read_sf("http://datos.cedeus.cl/geoserver/wfs?srsName=EPSG%3A4326&typename=geonode%3Aciclovias_sendasmultiproposito_existentes_rms_2019_gorerms&outputFormat=json&version=1.0.0&service=WFS&request=GetFeature")

mapview(ciclovias_2018, color = "purple")+
  mapview(ciclovias_2016, color = "orange")

Usando leafsync::sync()

library(leafsync)

c2018 <- mapview(ciclovias_2018, color = "purple")
c2016 <- mapview(ciclovias_2016, color = "orange")
sync(c2016, c2018)

También podemos usar rásters

library(raster)

temp_ene <- raster("data/temp_ene.tif")
temp_jul <- raster("data/temp_jul.tif")
region <- read_sf("data/metropolitana.geojson")

pal <- scales::brewer_pal(palette = "Spectral", direction = -1)

p1 <- mapview(temp_ene, at = seq(-30, 50, 10), na.color = "transparent", col.regions = pal(5))+
  mapview(region, col.regions = "transparent", alpha.regions = 0)

p2 <- mapview(temp_jul, at = seq(-30, 50, 10), na.color = "transparent", col.regions = pal(5))+
  mapview(region, col.regions = "transparent", alpha.regions = 0)

sync(p1, p2)